An Efficient Random Forest Classifier for Detecting Malicious Docker Images in Docker Hub Repository
Abstract: The number of exploits of Docker images involving the injection of adversarial behaviors into the image’s layers is increasing immensely. Docker images are a fundamental component of Docker.
Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.
A new technique breaks Dijkstra's 70-year-old record: it finds routes faster in huge networks, changing graph theory forever.
Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...
Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...
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Data-driven framework predicts electric vehicle range with improved real-world accuracy
"Range anxiety" remains one of the major issues of electric vehicles (EVs). Most of the existing range prediction technologies rely on simulated conditions or limited datasets, making it difficult to ...
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level ...
Abstract: Research and development of highly accurate falling detection systems (FDSs) for individuals with medical conditions or the elderly are crucial for mitigating the risks associated with falls ...
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